When given a Python project codebase, this skill helps the agent to set up virtual environments, install dependencies, and run scripts.
Installation
Details
Usage
After installing, this skill will be available to your AI coding assistant.
Verify installation:
skills listSkill Instructions
name: setup-env description: "When given a Python project codebase, this skill helps the agent to set up virtual environments, install dependencies, and run scripts."
Skill: Use uv to manage Python environments
Scope
- Create a virtual environment
- Install dependencies
- Run Python scripts/commands
Assume uv is already available on PATH.
Workflow selection
- If
pyproject.tomlexists: use project workflow (uv sync,uv run) - Else if
requirements.txtexists: use pip workflow (uv venv,uv pip install -r ...,.venv/bin/python ...) - Else: stop with an error ("No pyproject.toml or requirements.txt found.")
Project workflow (pyproject.toml)
Create venv + install dependencies
From the repo root (where pyproject.toml is):
uv sync
Notes:
- uv maintains a persistent project environment at
.venvand installs deps there.
Run scripts / commands (preferred)
Always run within the project environment:
uv run -- python <script.py> [args...]uv run -- python -m <module> [args...]
Notes:
uv runexecutes inside the project environment and ensures it is up-to-date.
Pip workflow (requirements.txt)
Create venv
From the repo root:
uv venv# creates.venvby default
Install dependencies
uv pip install -r requirements.txt
Run scripts / commands
Run using the venv interpreter directly (no activation required):
.venv/bin/python <script.py> [args...].venv/bin/python -m <module> [args...]
(uv will also automatically find and use the default .venv in subsequent invocations when you use uv pip ... commands.)
Minimal sanity checks (optional)
test -x .venv/bin/pythonuv pip list(verify packages installed)
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